The latest News and Information on Monitoring for Websites, Applications, APIs, Infrastructure, and other technologies.
As my co-founder Caleb Hailey likes to say, collecting monitoring and observability data is essentially a solved problem. The only remaining challenges are related to getting that data where you want it to go. When dealing with different formats — say, collecting Prometheus metrics and storing them in Elasticsearch — this can be a non-trivial problem. Put simply, it’s like trying to put a square peg into a round hole.
It’s been just over six months since Splunk disrupted the Application Performance Monitoring (APM) market with the launched SignalFx Microservices APM, combining the technologies of SignalFx and Omnition. We have pushed ourselves harder and continued to invest in creating more value for our customers by making it easier for them to ingest ALL data and providing ever more powerful analytics on top of that data.
Do you SPL? Well, if you do, you probably either already know about the job inspector, or you’re about to. Either way, you probably don’t know enough. Don’t worry though, that’s all about to change. There are a few different aspects of the job inspector that everyone should be familiar with. These include the execution costs, the search job properties, and the search.log. I’m going to walk us through these areas, and some others, and their importance.
StatsD is among the most popular monitoring solutions used to instrument code with the help of custom metrics. It has become very popular over the course of the last few years and emerged as the industry standard for open source inside-the-app monitoring. It has a host of advantageous features that makes it perfect for application performance measurements.
As promised in our latest update in June, we have prepared the new public status pages. We’ll deploy them after this beta period so your feedback will be much appreciated! What’s new, how does it look and how can you use it?
